Course Syllabus

Overview

Students should watch Canvas/Ed Lessons course videos according to the following schedule. It is recommended for students to do lab sessions on the schedule by yourself as early as possible since some of homework may cover the lab materials scheduled later than the homework. For the online video lectures, CS/CSE students should go to Udacity or Canvas to access to the sources.

Schedule

Week #DatesVideo lessonsLabDeliverable Due
1Jan 9-13[1. Intro to Big Data Analytics], [2. Course Overview]
2Jan 16-20[3. Predictive Modeling][Hadoop & HDFS Basics]HW1 Due (Jan 23)
3Jan 23-27[4.MapReduce]& [HBase][Hadoop Pig & Hive]
4Jan 30-Feb 3[5.Classification evaluation metrics], [6.Classification ensemble methods]HW2 Due (Feb 6)
5Feb 6-10[7. Phenotyping], [8. Clustering][Scala Basic], [Spark Basic], [Spark SQL]
6Feb 13-17[9. Spark][Spark Application] & [Spark MLlib]HW3 Due & Project Group Formation (Feb 20)
7Feb 20-24[10. Medical ontology][NLP Lab]
8Feb 27-Mar 3[11. Graph analysis][Spark GraphX]Project Proposal Due (Mar 6)
9Mar 6-10[12. Dimensionality Reduction], [13. Patient similairty], [14. CNN][Deep Learning Lab]HW4 Due (Mar 13)
10Mar 13-17[15. DNN], [16. RNN]
11Mar 20-24Project DiscussionHW5 Due (Mar 27)
12Mar 27- 31Project Discussion
13Apr 3-7Project DiscussionProject Draft Due (Apr 10)
14Apr 10-14Project DiscussionFinal Exam (Apr 17)
15Apr 17-21Project DiscussionFinal Project Due (code + presentation + final paper) (Apr 24)
16Apr 24-28Project Submission

Previous Guest Lectures

See RESOURCE section.